Model comparisons and model selections based on generalization criterion methodology
Journal of Mathematical Psychology
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
A Replicated Quantitative Analysis of Fault Distributions in Complex Software Systems
IEEE Transactions on Software Engineering
Local and Global Recency Weighting Approach to Bug Prediction
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Comments on "Data Mining Static Code Attributes to Learn Defect Predictors"
IEEE Transactions on Software Engineering
Predicting Defective Software Components from Code Complexity Measures
PRDC '07 Proceedings of the 13th Pacific Rim International Symposium on Dependable Computing
On the Distribution of Software Faults
IEEE Transactions on Software Engineering
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Are change metrics good predictors for an evolving software product line?
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Predicting defect numbers based on defect state transition models
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
An Empirical Analysis of Software Changes on Statement Entity in Java Open Source Projects
International Journal of Open Source Software and Processes
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We analyze the Eclipse defect data from June 2004 to November 2007, and find that the growth of the number of defects can be well modeled by polynomial functions. Furthermore, we can predict the number of future Eclipse defects based on the nature of defect growth.